| Literature DB >> 29514814 |
Grace Irimu1,2, Morris Ogero1, George Mbevi1, Ambrose Agweyu1, Samuel Akech1, Thomas Julius1, Rachel Nyamai3, David Githang'a4, Philip Ayieko1, Mike English1,5.
Abstract
Entities:
Keywords: hospital care; low-income country; networks; quality
Mesh:
Year: 2018 PMID: 29514814 PMCID: PMC6278651 DOI: 10.1136/archdischild-2017-314348
Source DB: PubMed Journal: Arch Dis Child ISSN: 0003-9888 Impact factor: 3.791
Examples of the challenges encountered during the implementation of the Clinical Information Network related to preservice training, hospital norms and national policies
| Level | Examples of challenges |
| Preservice training | The training of junior medical staff sometimes conflicts with the apparent restrictions on clinical autonomy encompassed by guidelines and their learning experience in tertiary settings where evidence-based guidelines may be looked down on as ‘too simple’. |
| Hospital contexts and practical norms | Hospitals often lacked printers/projectors making wide dissemination of feedback reports problematic with a continued reliance on receipt of limited numbers of hard copies. that there is little value in writing a short summary of events around the time of death and recording the primary and contributory diagnoses; that ascertaining HIV status should be done by specific HIV counsellors, not clinicians; that anthropometric measurements should be performed by nutritionists, not clinicians; unavailability of some essential services at night and weekends, for example, inaccessibility of special feeds for malnutrition undermining guideline adherence. |
| National/county | Historically weak systems for disseminating policies and monitoring their uptake linked to weak systems for promoting and regulating quality of care. |
Figure 1Scatter plot showing each hospital’s performance in documentation (grey circular markers) based on the mean of all patient scores in each month from first month to the 34th month of joining the Clinical Information Network for each site. Each variable (fever, cough, difficulty breathing, diarrhoea, vomiting, convulsions, weight, oedema, stridor, respiratory rate, grunting, chest indrawing, acidotic breathing, wheeze, crackles, temperature gradient, pulse character, capillary refill time, skin pinch duration, sunken eyes, pallor, central cyanosis, disability scale (Alert, Voice, Pain, Unresponsive (AVPU)), ability to drink, stiff neck) is given a score of 1; each patient record is then given a score out of 25 and the mean score calculated for all patients in that month. The solid central trend line with black dots represents the median value of the 14 hospital-specific observations and the upper and lower grey trend lines represent the upper and lower IQRs of the 14 hospital-specific observations, respectively.
Figure 2Scatter plots showing each hospital’s performance in documentation (grey circular markers) each month from March 2014 to November 2016 for a clear primary discharge diagnosis for ages 0–12 years (A) and HIV status for all admissions aged 0–12 years (B) both with target documentation rate at 80%. Panel (C) illustrates documentation of blood glucose test results for all patients aged 0–12 years with any danger sign with target of 60%. The solid central trend line with black dots represents the median value of the 14 hospital-specific observations and the upper and lower grey trend lines represent the upper and lower IQRs of the 14 hospital-specific observations, respectively.
Figure 3Scatter plots showing each hospital’s performance in documentation (grey circular markers) each month from March 2014 to November 2016 for documentation of mid-upper arm circumference (MUAC) for all admissions aged 6–59 months (A) and documentation of oxygen saturation of all admissions aged 1 month to 12 years (B). The solid central trend line with black dots represents the median value of the 14 hospital-specific observations and the upper and lower grey trend lines represent the upper and lower IQRs of the 14 hospital-specific observations, respectively.